Article

The Eﬀects of Dietary Intervention and Macrophage-Activating
Factor Supplementation on Cognitive Function in Elderly Usersof Outpatient Rehabilitation
Yoko Uchiyama-Tanaka 1,*, Hajime Yamakage 2 and Toshio Inui 3
Yoko Clinic, 3-3-13 Takami, Yahatahigashiku, Kitakyushu 805-0016, Fukuoka, Japan
Satista Co., Ltd., 77-1, Minamiochiai, Makishimama-cho, Uji 611-0041, Kyoto, Japan; yamakage@satista.jp
3 Inui Clinic, 3-34, 8-2, Okubo-cho, Moriguchi 570-0012, Osaka, Japan; inuicl@yahoo.co.jp* Correspondence: yoko-uchiyama-tanaka@yoko-clinic.net
1
2

Citation: Uchiyama-Tanaka, Y.;
Yamakage, H.; Inui, T. The Eﬀects ofDietary Intervention andMacrophage-Activating Factor
Supplementation on Cognitive
Function in Elderly Users of
Outpatient Rehabilitation. Nutrients
2024, 16, 2078. https://doi.org/
10.3390/nu16132078
Academic Editor: Mario Barbagallo
Received: 24 May 2024

Abstract: Background: Age, genetic, and environmental factors are noted to contribute to dementia
risk. Neuroplasticity, protection from degeneration and cell death, and early intervention are desirable for preventing dementia. The linkage between neurons and microglia has been a research focus.
In this study, we examined the eﬀects of dietary modification (a reduction in advanced glycation
end products [AGEs]) and macrophage-activating factor (MAF; a macrophage regulator) supplementation on cognitive function in elderly participants undergoing rehabilitation. Methods: Participants were older than 60 years of age and had been attending a daycare rehabilitation facility for atleast three months without cognitive dysfunction, severe anemia, terminal cancer, or neurodegenerative diseases such as Parkinson’s disease. The exercise protocol at the rehabilitation facility was
not changed during the study period. Forty-three participates were randomly divided into threegroups: a control group receiving placebo, a group receiving dietary guidance, and a group receiving dietary guidance and MAF supplementation. The amyloid-β40/42 ratio, dietary AGE intake,plasma AGE levels, dietary caloric intake, and mild cognitive impairment (MCI) screen test were
evaluated. Results: Four participants withdrew from the study. MCI screening scores significantly
improved in the MAF supplementation group, especially after 6 months. Dietary modulation was
also more eﬀective than placebo at improving cognitive function after 12 months. Only the control
group exhibited significantly increased plasma AGEs while the dietary modulation and MAF supplementation groups showed no change in plasma AGEs after 12 months. Conclusions: MAF supplementation improved cognitive function, especially after 6 months, in elderly people undergoingrehabilitation. Dietary modulation was also eﬀective for improving cognitive function after 12months compared to that in the control group. It was diﬃcult to supervise meals during dietary
guidance at the daycare service. However, simple guidance could show improvements in cognitive
function through diet.
Keywords: dementia; cognitive function; macrophage; AGEs; amyloid beta

Revised: 24 June 2024
Accepted: 26 June 2024
Published: 28 June 2024

1. Introduction
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution

(CC

BY)

license(https://creativecommons.org/licenses/by/4.0/).

Multiple factors have been identified as associated with dementia risk, including age,
genetic factors, and environmental factors (lifestyle, exercise, toxin exposure, diet, nutrition, social involvement, hearing, and educational history) [1–3]. These factors are believed to trigger protein misfolding, synaptic dysfunction, reactive oxygen species, mitochondrial dysfunction, impaired calcium regulation in cytoplasm, and decreased cellnumber, resulting in neurodegeneration [1,4,5]. With ageing of the population and an increase in the prevalence of diabetes and atherosclerosis, the prevalence of dementia is on
the rise. The Global Burden of Disease (GBD) Dementia Forecasting Collaborators indicate

Nutrients 2024, 16, 2078. https://doi.org/10.3390/nu16132078

www.mdpi.com/journal/nutrients

Nutrients 2024, 16, 2078

2 of 16that the prevalence of dementia will reach 150 million by 2050 [6]. If mild cognitive impairment is included in this estimation, the number will be even greater.
Dementia was once thought to be a progressive disease in which cognitive function
could not be improved or recovered. However, there are also emerging reports that improvements in the causes of brain inflammation and amyloid-β accumulation may improve symptoms even after a diagnosis of dementia [1,7,8]. Once dementia is diagnosed,organic changes in the brain progress, and recovery is, however, diﬃcult. Therefore, preventing the onset of dementia is highly important. Exercise, a healthy diet, social stimulation, intestinal environment improvement, lifestyle modification, optimal sleep, stresscare, hearing aids, nutritional supplementation, and other supplements have been reported to be eﬀective in dementia prevention [1,7].
Notably, brain inflammation is involved in cognitive dysfunction. The linkage between neurons, microglia, and astrocytes has been noted in brain synapse loss, the removal of waste products such as amyloid-β, the control of infection and inflammation,
synapse germination, neurogenesis, and pruning [4,5,9–14]. Microglia were previously
thought to be structural factors in the brain but have been shown to have macrophagefunctions [4,12]. Microglial dysfunction is a problem in degenerative brain diseases[4,5,10,11]. Enriched protein homeostasis, inflammation, and metal ion homeostasis pathways were observed in astrocytes in animal studies of Alzheimer’s disease. Phagocytosis,
inflammation, and proteostasis pathways were enriched in tissue amyloid-rich microglia
and perivascular macrophages. The diversity of glial transcription in Alzheimer’s and the
response of both astrocytes and microglia to pathological protein clearance and inflammation are associated [15]. In another animal model with neuroinflammatory diseases,
Bonneh-Barkay et al. showed that cytokines released from macrophages elevated YKL-40,
a marker of inflammation, in astrocytes. This phenomenon is observed among components in the CNS environment. The network of peripheral macrophages, centrally locatedperivascular macrophages, astrocytes, and microglia may, therefore, be important. Activating ageing macrophages may be important for reducing inflammation and waste accumulation [16].
Group-specific component macrophage activation factor (GcMAF) is a protein that
results from the sequential deglycosylation of its precursor, vitamin-binding protein(VDBP) [17,18]. The Gc protein VDBP is produced in the liver and is present in the majority of biological fluids. VDBP has multifunctional properties as a transporter of serum
vitamin D3 and its metabolites, functions as an actin scavenger during cellular injury, acts
as a chemotaxin for phagocytic cells, and plays a role in macrophage activation as a precursor for GcMAF. This Gc protein has a triple-domain modular structure, where domain
III (the C-terminal end) harbors a single glycosylation site. The terminal N-acetylgalactosamine (GalNAc) moiety in domain III is the region involved in the GcMAF-mediated macrophage activation cascade. During inflammation, lysophosphatidylcholine is released
from tissue, which induces the expression of beta-galactosidase in B cells and sialidase in
T cells. These enzymes hydrolyze the terminal galactose and sialic acid saccharides of the
Gc protein to convert it into GcMAF with an N-acetylgalactosamine moiety [17,19]. Oneof the cell types targeted is resident intestinal macrophages, which exhibit great phagocytic activity without initiating an inflammatory response due to their low, or even absent,
expression of innate response receptors, including receptors for lipoplysaccharides (LPS)(CD14), Fcα (CD89), Fcγ (CD64, CD16), and CR3 (CD11b/CD18). Resident intestinal macrophages constitute the largest pool of macrophages in the body. These cells are able todownregulate an excessive systemic inflammatory response by driving the resolution of
inflammation and by contributing to a mechanism of oral tolerance to foreign antigens, aswell as autoantigens.
MAF was discovered to be a macrophage activator but has also been shown to regulate macrophage function, improve allergies, and optimize immune function, for example,
providing adjuvant therapy against cancer and many other diseases [17]. Furthermore, inanimal experiments with MAF, recovery from brain damage (embolization model [20] andNutrients 2024, 16, 2078

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trauma model [21]) and a reduction in amyloid-β have been observed, and clinically, theeﬀectiveness of MAF has been shown in autism spectrum disorder [22] and multiple sclerosis [23], where brain inflammation is suggested. However, the eﬀects of MAF on cognitive function have not yet been studied.
In examining the eﬀects of supplements, it is important to first consider diet. There
are many reports that dietary improvements improve cognitive function, and among
these, reports on advanced glycation end products (AGEs) and cognitive function haveattracted increasing amounts of attention. AGEs are formed by nonenzymatic reactions
between sugars and amino groups of macromolecules, such as proteins, lipids, and nucleic
acids [24]. Because glycation occurs constantly during normal ageing and the rate of degradation of glycated macromolecule derivatives is very slow, AGEs accumulate with increasing age. Accumulating evidence shows that AGEs play important roles in the development of age-related disorders, including diabetic vascular complications, osteoporosis,
and Alzheimer’s disease [24–27]. It is estimated that 6–7% of AGEs are taken up by the
body from exogenous sources (diet, tobacco, physical activity, etc.) [28,29].
In this study, we examined the eﬀects of nutritional guidance (reducing the amountof AGEs in the diet as much as possible) and MAF supplementation on cognitive function
in a group of elderly individuals attending a day rehabilitation facility (that is, elderly
individuals who were able to exercise regularly). This study was double-blind with respect to the drug intervention but open with respect to the presence or absence of dietary
guidance.
2. Methods
2.1. Study Design and ParticipantsThis was a single-center, randomized controlled, open-label, parallel-arm trial. Individuals older than 60 years of age who were not diagnosed with dementia, were in stablecondition, and had been attending Soushinkai, a daycare rehabilitation facility in Okayama, for at least three months were eligible for inclusion. The procedures for human experimentation were conducted in accordance with the guidelines of the Declaration of
Helsinki (2000), and informed consent was obtained from all subjects.
At the time of entry, interviews, evaluations, blood tests, and medical examinations
were conducted. Patients with cognitive dysfunction, severe anemia, terminal cancer, orneurodegenerative diseases such as Parkinson’s disease were excluded. Soushinkai rehabilitation facilities provide not only passive rehabilitation but also voluntary rehabilitation, visitation, and assistance so that rehabilitation can be performed at home. The facility
also has a daycare center and exercise machines.
Between May 2022 and July 2022, a total of 43 people (mean age 79.0 ± 8.8 years, 17
men and 26 women, care level of support to care level 3) participated in the study. Of
these, 15 were allocated to Group C, a normal rehabilitation-only group as a control group;
14 were allocated to Group D, a dietary guidance group, who received dietary guidance
and rehabilitation by the same physician; and 14 were allocated to Group M, who received
one capsule of MAF triple in the morning upon waking and one capsule before bedtime,
and the same dietary guidance as Group D (Figure 1). Groups C and D received placeboin the same manner, with one capsule upon waking and one capsule before bedtime.

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Figure 1. Flowchart of this study. Group M: the MAF triple group; Group D: the diet group; Group
C: the control group; FAS: full analysis set; PPS: per protocol set; MI: myocardial infarction.

MAF triple capsules are dietary supplements produced by Saisei Pharma, Osaka, Japan, which are designed to modulate the mucosal immunity of the intestine. This facility
teaches exercise according to the level of care, and the randomization was statisticallyvalid for all three groups in terms of the level of care. Additionally, the patients had tohave been visiting the facility for at least three months, be in stable condition, and nothave changed their protocol of exercise during the study period unless there was a special
reason for doing so.
Before assessing the mild cognitive impairment screening (MCIS) score, AGE levels
were measured with an AGE reader. The plasma amyloid-β 40/42 ratio, general blood parameters (peripheral blood, glutamate oxaloacetate transaminase (GOT), glutamate pyruvate transaminase (GPT), gamma GPT, alkaline phosphatase (ALP), hemoglobin (Hb)
A1C, blood urea nitrogen (BUN), creatine (Cr), uric acid, total cholesterol, high-density
lipoprotein (HDL) cholesterol, triglycerides, ferritin, 25OH vitamin D, C-reactive protein(CRP), free thyroxine (T)4, thyroid-stimulation hormone (TSH), albumin, zinc, copper,

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sodium, potassium, chloride, folic acid, vitamin B12, and vitamin B1), and dietary AGE
intake were measured. The same procedure was used after 6 and 12 months. This study
was approved by the Saisei Mirai Ethics Committee (No. 2022-001).
2.2. Randomization
After screening, the data of each participant were linked to the participant identification code provided and anonymized. Next, the participants were randomized to Groups
M, D, and C at a ratio of 1:1:1. Randomized allocation was performed via the simple randomization method. The allocation table was generated and maintained by a third party
at the facility who was not involved in the study.
2.3. Dietary Guidance
Dietary guidance was provided to reduce the amount of AGEs in the diet as much as
possible. It is generally known that AGEs are produced in large amounts when meat products and fat-rich foods are fried or baked at high temperatures. On the other hand, cooking
methods such as slow steaming or boiling of foods with a high-water content are lesslikely to produce AGEs, which have long been known to be produced in Maillard reactions or browning reactions. The browning of foods is a rough indication of their AGE
content. Fructose is approximately 10 times more likely to form AGEs than glucose. It isthought that avoiding drinking carbonated beverages that contain a large amount of fructose corn syrup, avoiding excessive consumption of fructose, and avoiding consuming
foods with significant browning can reduce the amount of exogenous AGE intake [30].
Lemon and vinegar can also reduce the formation of AGEs during the cooking process. A
well-balanced diet rich in vegetables, seaweed, and mushrooms is also recommended [31].
First, all groups were asked to describe their meals for one week, or if they were unable to do so, they were asked to do so with the help of their family members, who wereinterviewed in more detail by a nutritionist. Calorie calculations were then performed.
AGE calculations were performed with the exAGE formula devised by the AGE Research
Association. These calculations were performed before the study and at 6 months. For
Group D and Group M, at the start of the study, materials were first distributed to thegroup, and dietary guidance was given by the same physician in the form of a lecture. The
same doctor showed them pictures and instructed them to eat less processed meat (sausage, bacon, etc.), packaged foods, deep-fried foods, sugary sweets, and snacks, and moresteamed foods, fresh vegetables, and fruits. Participants were asked to take home the materials used in the information sessions and share the information with their household
members. Afterward, during the individual interviews, we provided advice on what tomaintain and what to add to the diet of each person based on a dietary chart. Individualinterviews were held at the start of the study, at 6 months, and at 12 months. In addition
to the doctor’s interviews and check-ins, the dietitian interviewed them monthly to ensurethat the dietary instructions were being followed and that they were doing well.
2.4. Calculation of AGEs in the Diet
The carboxymethyllysine (CML; a type of AGE) coeﬃcient is determined by dividing
foodstuﬀs into 18 categories, including grains, meats, fats, oils, and vegetables, and multiplying the coeﬃcient of cooking (one for raw foodstuﬀs and one for boiled or baked
foodstuﬀs) by the coeﬃcient of each category. The following original formula is used toestimate the CML (AGE) content of food products:
CML content (in kilograms) = total protein and fat content (g) per 100 g of food material × processing factor × cooking factor × CML factor. This formula was derived by determining the protein and fat contents of ingredients from the Japanese Food Composition
Table. There was a strong positive correlation (p < 0.0001) between the measured CML
content in foods reported by Uribarri et al. and the estimates obtained in the four factors

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described above, with a correlation coeﬃcient of 0.52. The average CML intake for theAmerican population is reported to be approximately 15,000 KU [29].
2.5. Cognitive Function Assessment
The MCIS was used because it is applicable for those with dementia or mild dementia. The MCIS, derived from the Word List Memory test, diﬀerentiates cognitive changes
associated with normal ageing from mild cognitive impairment as well as dementia [32].
The MCIS is a brief, electronically scored, verbally administered test that uses correspondence analysis to calculate an individual’s memory capabilities, which is then reported asa Memory Performance Index [33–35]. The MCIS has been validated in both academic andcommunity clinical settings and in multiple languages [36,37]. Testing was performed before the start of the study and at 6 and 12 months. Since large social fluctuations in participants have a direct impact on the score, this index is best for use in studies of populations
without large social fluctuations.
2.6. AGE Measurement
Glycation levels were measured on the dominant volar forearm using an AGE Reader
mu (Diagnoptics Technologies B. V., Groningen, The Netherlands) [38,39]. Pentosidine
and crossline have structural properties that cause them to emit fluorescent light across a
specific range of wavelengths upon excitation by ultraviolet light. This unique characteristic has been used to develop technology that quantifies the accumulated AGEs withinhuman skin. Although several confounding factors exist, such as other fluorophores, skincare cream use, and skin pigmentation, skin autofluorescence (SAF) is a prominent biomarker that may reflect tissue accumulation of AGEs [28,40,41]. Certain types of AGEs
autofluoresce when exposed to ultraviolet light. The AGE Reader illuminates skin withultraviolet light (excitation range = 300–420 nm) and then detects the resulting fluorescentlight (emission range = 420–600 nm) while simultaneously detecting light reflected fromthe skin in the 300 to 420 nm range. The SAF, reported in arbitrary units, is defined as theratio of the intensity of the emitted fluorescent light to that of the reflected light [29,42,43].
2.7. Plasma Ratio of Amyloid-β40 to Amyloid-β42
Recent technological advancements in mass spectrometry have led to improvements
in instrument sensitivity and precision, resulting in the development of improved plasma
amyloid-beta (Aβ) assays. Many studies have reported encouraging results for plasma Aβ
as a biomarker for Alzheimer’s disease. Tests for the risk of developing dementia wereconducted at the starting, 6-month, and 12-month time points [44].
2.8. Sample Size
The study protocol was designed to detect a large eﬀect size (eﬀect size = 0.8) between
groups for the change in endpoint over the 12-month study period. Based on that assumption and for a power of 80% and a 5% significance level, the sample size was calculated to
be 13 participants per group.
2.9. Statistical Methods
All of the data were analyzed based on the intention-to-treat principle. The primary
analysis was performed on the full analysis set (FAS), while the MCIS, which is heavily
influenced by social variables, was evaluated in the per protocol set (PPS). The absolute
standard diﬀerence (ASD) was used to assess the balance of patient backgrounds by random assignment, and the ASD was considered balanced if the 95% confidence interval inthis population was less than 0.755 as a threshold value that did not cross zero.
The repeated-measures endpoints were analyzed with linear mixed models that included intervention, dummy variables for time, intervention-by-time interactions, andbaseline parameters of endpoints as covariates and participants as a random eﬀect. The

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covariance structure was a completely general covariance matrix. The results are reported
as the least squares means with 95% confidence intervals (CIs) at each time point. A pvalue < 0.05 was considered to indicate statistical significance, and all p values were twosided with multiplicity adjustment by the Bonferroni method. All of the statistical analyses were performed using SPSS version 24.0 (IBM Japan, Ltd., Tokyo, Japan).
3. Results
A total of 43 people (mean age 79.0 ± 8.8 years, 17 men and 26 women, care level of
support to care level 3) participated. Of these, 15 were allocated to Group C, 14 were allocated to Group D, and 14 were allocated to Group M (Figure 1). In Group D, one participant took donepezil hydrochloride after randomization, and this participant was subsequently excluded from the FAS. In Group C, one participant had a myocardial infarction
and discontinued use of the facility, and in Group D, two participants voluntarily withdrew from the study. In Group C, three participants experienced major social changes
during the study period. Thus, the resulting PPS included 12 participants in Group C, 13participants in Group D, and 14 participants in Group M.
The clinical characteristics of the participants are shown in Table 1. The ASD was lessthan 0.755 (the threshold for which the 95% CI for the ASD did not cross 0 in this study),
indicating that the baseline characteristics (age, sex, level of care, presence of diabetes,smoking status, history of education, cognitive function according to the MCIS score,
AGEs, the amyloid-β 40/42 ratio, AGE levels, and calories) of the three groups were similar.
Table 1. Baseline characteristics in the study.
Group M
14

Group D13Group C
15

Male
Femalemean ± SD
mean ± SD

5, 35.7%
9, 64.3%
80.8 ± 10.3
12.1 ± 1.8

5, 38.5%
8, 61.5%
78.5 ± 10.1
12.7 ± 2.1

7, 46.7%
8, 53.3%
77.8 ± 6.8
12.2 ± 2.2

Support Needed
Care Needed
Support: level 1
Support: level 2
Care: level 1
Care: level 2
Care: level 3
Care: level 4
yes
yes

11, 78.6%
3, 21.4%
3, 21.4%
8, 57.1%
0, 0.0%1, 7.1%2, 14.3%
0, 0.0%2, 14.3%
0, 0.0%10, 76.9%
3, 23.1%
0, 0.0%10, 76.9%
1, 7.7%2, 15.4%
0, 0.0%0, 0.0%5, 38.5%0, 0.0%9, 60.0%
6, 40.0%
2, 13.3%
7, 46.7%
0, 0.0%3, 20.0%
2, 13.3%
1, 6.7%
6, 42.9%
1, 6.7%n (in FAS)
Gender [n, %]Age [years]
Years of education [years]
Nursing care level [n, %]Diabetes mellitus
Current smoker
Baseline parameters
MCIS
AGE
Aβ40/42dietary AGEs
Calories in diet

ASD
0.224

0.342
0.307
0.411

0.667
0.379

mean ± SD
46.4 ± 16.5
47.2 ± 12.2
44.2 ± 13.9
0.230
mean ± SD
2.7 ± 0.6
2.5 ± 0.5
2.7 ± 0.5
0.269
mean ± SD
10.1 ± 2.0
9.7 ± 1.7
10.5 ± 1.7
0.483
mean ± SD
11,914 ± 4632
12,287 ± 7108
11,530 ± 3513
0.135
mean ± SD
1564 ± 272
1626 ± 297
1550 ± 272
0.266Group M (M): the MAT triple group; Group D (D): the diet group; Group C (C): the control group.
SD: standard deviation; ASD: absolute standardized diﬀerence; FAS: full analysis set; MCIS: themild cognitive impairment screen; AGEs: advanced glycation end products; Aβ40/42: plasma amyloid beta 40/42 ratio.

The results of the analysis of outcomes for the FAS are shown in Table 2. Dietarycaloric intake did not change before or after the intervention in any group, and there wereNutrients 2024, 16, 2078

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no significant group diﬀerences in dietary caloric intake during the intervention (Figure2). Dietary AGEs were unchanged in Group C but decreased significantly in Group D(−2378 [95% CI: −4724 to −32] KU). Dietary AGEs were unchanged in Group M despite the
dietary guidance, and there were no significant group diﬀerences in intervention eﬀects(Figure 3). There was not much change in diet in Group M, perhaps because some of theresidents were having their meals prepared by their housemates, matching meals with
their roommates, or having meals served at other daycares. In addition to diet, there wereno significant diﬀerences in smoking history and exercise load (nursing care level), whichhave a significant influence on AGEs in this study (Table 1).

Figure 2. Line and bar graphs of intervention eﬀects on daily caloric intake. Line graphs: Leastsquare (LS) mean and 95% confidence interval (CI) of daily calories at each measurement point foreach group are shown. The results of the comparison test between measurement points for eachgroup are shown. Bar graphs: LS means and 95% CIs of daily calories changes from baseline at eachmeasurement point in each group are shown. The results of comparison tests between intervention
groups are shown. Analysis method: repeated measures linear mixed model with subjects as a variable [model including initial dependent values as covariates]. Group M: the MAF triple group;Group D: the diet group; Group C: the control group; n.s.: not significant.

Figure 3. Line and bar graphs showing the eﬀects of the interventions on dietary AGEs. Line graphs:
Least square (LS) means and 95% confidence intervals (CIs) of dietary AGE measurements at eachmeasurement point for each group are shown. The results of the comparison test between measurement points for each group are shown. Bar graphs: LS means and 95% CIs of dietary AGE changes
from baseline at each measurement point in each group are shown. The results of comparison tests
between intervention groups are shown. Analysis method: repeated measures linear mixed modelwith subjects as a variable (model including initial dependent values as covariates). Group M: the
MAF triple group; Group D: the diet group; Group C: the control group; n.s.: not significant.

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Table 2. Endpoints analysis using mixed models.

MCIS
Baseline
At 6-month
Change at 6-month
At 12-month
Change at 12-month
AGE
Baseline
At 6-month
Change at 6-month
At 12-month
Change at 12-monthAβ40/42
Baseline
At 6-month
Change at 6-month
At 12-month
Change at 12-monthdietary AGEs
Baseline
At 6-month
Change at 12-month
Calories, daily
Baseline
At 6-month
Change at 6-month

LSM

Group M
95% CI

46.65
55.79
9.14
55.71
9.06

43.51 to 49.79
52.65 to 58.93
4.70 to 13.58
52.45 to 58.97
4.53 to 13.59

2.70
2.62
−0.08
2.57
−0.13

2.54 to 2.86
2.47 to 2.78
−0.26 to 0.10
2.42 to 2.73
−0.31 to 0.05

10.12
9.50
−0.63
8.84
−1.28

9.55 to 10.69
8.92 to 10.07−1.51 to 0.26
8.25 to 9.43
−2.18 to −0.38

12,003
10,975−1029

10,775 to 13,232
9747 to 12,203−3044 to 986

p*

LSM

Group D
95% CI<0.001

46.73
46.52
−0.21
54.09
7.36

43.47 to 49.99
42.98 to 50.06−5.03 to 4.60
50.37 to 57.81
2.42 to 12.30

2.69
2.72
0.03
2.64
−0.05

2.51 to 2.86
2.55 to 2.90
−0.17 to 0.23
2.47 to 2.82
−0.25 to 0.16

0.006

9.89
9.39
−0.50
8.50
−1.39

9.29 to 10.49
8.68 to 10.09−1.50 to 0.49
7.85 to 9.15
−2.34 to −0.44

0.307

12,0439665−2378

10,717 to 13,370
8062 to 11,268−4724 to −32<0.001

0.391
0.164

0.163

p*

LSM

Group C
95% CIp*

M vs. Cp **D vs. CM vs. D

0.933

46.62
48.61
1.99
46.71
0.10

43.22 to 50.01
45.06 to 52.15−2.91 to 6.90
42.99 to 50.44−4.93 to 5.13

0.422

0.035

0.526

0.008

0.969

0.010

0.044

0.624

2.71
2.81
0.10
3.08
0.37

2.53 to 2.88
2.64 to 2.98
−0.10 to 0.31
2.90 to 3.25
0.17 to 0.57

0.300

0.181

0.616

0.410

<0.001<0.001

0.005

0.538

9.81 to 10.92
9.08 to 10.22−1.58 to 0.15
8.38 to 9.53
−2.28 to −0.54

0.106

0.889

0.754

0.856

0.005

10.36
9.65
−0.71
8.95
−1.41

0.002

0.839

0.975

0.871

0.047

11,821
10,893−928

10,592 to 13,050
9620 to 12,166−2968 to 1112

0.363

0.944

0.352

0.383

0.005

0.740
0.656

0.316

1580
1490 to 1670
1600
1503 to 1698
1574
1486 to 1661
1581
1492 to 1672
1669
1548 to 1790
1605
1514 to 1695
1−138 to 142
0.980
69−97 to 235
0.410
31−168 to 106
0.651
0.765
0.726
0.538
Group M (M): the MAT triple group; Group D (D): the diet group; Group C (C): the control group. MCIS: the mild cognitive impairment screen; AGE: advanced
glycation end products; Aβ40/42: plasma amyloid beta 40/42 ratio; LSM: least square mean; 95% CI: 95% confidence interval. Analysis method: repeated measureslinear mixed model with subjects as a variable (model including initial dependent values as covariates). p *: Pairwise comparison with baseline values. p **: Pairwise
comparison between intervention groups for changes from baseline values.

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Only Group M had significantly improved MCIS scores after 6 months compared tobefore the study (from 46.65 [43.51 to 49.79] to 55.79 [52.65 to 58.93], a change of +9.14 [4.70
to 13.58]) in the PPS. The MCIS score of Group M also improved significantly comparedto that of both Group C and Group D (p = 0.035 and 0.008, respectively). Even after 12months, Group M maintained the improvement in cognitive function (55.71 [52.45 to
58.97]; a change of +9.06 [4.53 to 13.59]). Compared with before the study, Group D exhibited significant improvements in the MCIS score at 12 months (from 46.73 [43.47 to 49.99]
to 54.09 [50.37 to 57.81]; a change of +7.36 [2.42 to 12.3]). Compared with those in GroupC, the MCIS scores in Group M and Group D improved significantly at 12 months (p =0.010 and 0.0044, respectively) (Figure 4).

Figure 4. Line and bar graphs of intervention eﬀects on the mild cognitive impairment screen(MCIS). Line graphs: Least square (LS) means and 95% confidence intervals (CIs) of the MCIS measurements at each measurement point for each group are shown. The results of the comparison test
between measurement points for each group are shown. Bar graphs: LS means and 95% CIs of MCIS
changes from baseline at each measurement point in each group are shown. The results of comparison tests between intervention groups are shown. Analysis method: repeated measures linear
mixed model with subjects as a variable (model including initial dependent values as covariates).
Group M: the MAF triple group; Group D: the diet group; Group C: the control group.

The AGE level measured by an AGE reader did not change significantly in Groups
M or D at 6 months or at 12 months in the FAS. Only the AGE level of Group C significantly
increased at 12 months (from 2.71 [2.53 to 2.88] to 3.08 [2.90 to 3.25]; a change of +0.37 [0.17
to 0.57]). The AGE level in Group C at 12 months was significantly greater than that inGroup M and Group D (p < 0.001 and 0.005, respectively) (Figure 5).

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Figure 5. Line and bar graphs of the eﬀects of the intervention on advanced glycation end products(AGEs). Line graphs: Least square (LS) means and 95% confidence intervals (CIs) of AGE measurements at each measurement point for each group are shown. The results of the comparison test
between measurement points for each group are shown. Bar graphs: LS means and 95% CIs of AGE
changes from baseline at each measurement point in each group are shown. The results of comparison tests between intervention groups are shown. Analysis method: repeated measures linear
mixed model with subjects as a variable (model including initial dependent values as covariates).
Group M: the MAF triple group; Group D: the diet group; Group C: the control group; n.s.: notsignificant.

The plasma amyloid-β 40/42 ratio showed no significant diﬀerence at 6 months, but
at 12 months, the plasma amyloid-β 40/42 ratio of all of the groups decreased significantly
compared to that before the study (Group C, a change of—1.41 [−2.28 to −0.54]; Group D,a change of—1.39 [−2.34 to −0.44]; Group M, a change of—1.28 [−2.18 to −0.38]). There wereno significant diﬀerences in serum amyloid beta levels between the intervention groups(Figure 6).

Figure 6. Line and bar graphs of intervention eﬀects on the plasma amyloid beta 40/42 ratio(Aβ40/42). Line graphs: Least square (LS) means and 95% confidence intervals (CIs) of the Aβ40/42
measurements at each measurement point for each group are shown. The results of the comparison
test between measurement points for each group are shown. Bar graphs: LS means and 95% CIs of
Aβ40/42 changes from baseline at each measurement point in each group are shown. The results ofcomparison tests between intervention groups are shown. Analysis method: repeated measures linear mixed model with subjects as a variable (model including initial dependent values as covariates).
Group M: the MAF triple group; Group D: the diet group; Group C: the control group; n.s.: notsignificant.

Administration of MAF supplements not only prevented but also improved cognitive
decline after 6 months, and the eﬀect was maintained after 12 months. However, Group
D, in which participants received dietary guidance, showed improvements in cognitive
function after 12 months. The significant diﬀerences between Groups M and D disappeared after 12 months. However, compared to the control group, the dietary guidanceand MAF-treated groups both showed significant diﬀerences in cognitive function. Glycation levels tended to decrease in the MAF-treated group, but no significant pre- or posttreatment diﬀerences were observed. The control group showed a worsening (i.e., increasein) of AGE levels, with a significant diﬀerence between the dietary guidance group andthe MAF-treated group. The amyloid-β 40/42 ratio decreased significantly in all threegroups after 12 months compared to that at the start of the study. No adverse events occurred as a result of taking MAF supplements or receiving dietary guidance.

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4. Discussion
In this study, the administration of MAF supplements improved cognitive function.
Microglia play complex roles that are both beneficial and detrimental to disease pathogenesis, including engulfing or degrading toxic entities such as amyloid plaques and promoting neurotoxicity through excessive inflammatory cytokine release [4,9]. Aberrationsin the normal homeostatic functions of microglia, such as surveillance, synaptic pruning,and plasticity, may also contribute to excessive synapse loss and cognitive dysfunction inpatients with Alzheimer’s disease and other diseases [5,14]. Failure to clear apoptotic cells,
cellular debris, and toxic proteins, such as amyloid-β, can contribute to inflammation andneurodegeneration [13,14]. Synapse loss is an early hallmark of Alzheimer’s disease andother neurodegenerative disorders and is considered a strong correlate of cognitive decline. Numerous studies have demonstrated that microglia have many physiological, noninflammatory functions that are crucial for the central nervous system and for regulatingneuroplasticity, such as driving neural programmed cell death and synaptic plasticity inadults. Microglia have highly dynamic processes and continually survey their local environment. It is estimated that resident microglia scan the entire volume of the brain as oneof their homeostatic functions [14]. Other possible functions of resident microglia include
trauma site reduction in post-trauma model mice, amyloid-β plaque and phospho-tau tangle reduction, the repair of infarction in animal models, macrophage activation, and
VEGF-increasing eﬀects [20].
Macrophages work in both inflammatory and anti-inflammatory directions, but according to research of Uto et al., [20] the activation of anti-inflammatory macrophages
increases when inflammation is high, suggesting that macrophage function is not regulated in one direction but rather changes according to the situation. Siniscalco et al. [22]also reported that GcMAF aﬀects the endocannabinoid system, which controls cell-to-cellcommunication in, for example, greed, pain, immune regulation, emotional regulation,
motor function, development, ageing, neuroprotection, cognitive function, and memory.
No side eﬀects were reported after taking MAF supplements in this study. These MAF
supplements are made from whey and may cause allergic reactions in people with milkallergies. Few side eﬀects have been reported, but a few percent of people complained ofdiarrhea.
It is recognized that a high degree of glycation is associated with cognitive function[26,27]. The glycation level is related to exercise, smoking status, and age. AGEs essentially
increase with age. Therefore, the fact that only the control group showed a worsening of
AGE levels may be attributed to the eﬀects of MAF and dietary guidance (Figure 5). However, only Group D showed a decrease in dietary AGEs, while Group M did not (Figure3). This finding may be because the meals of many participants in Group M were cooked
by day service users or family members, and many participants did not cook for themselves.
Unintentionally, this study was conducted with Group C participants receiving an
exercise-only intervention, Group D receiving an exercise and dietary modification intervention, and Group M receiving an exercise and MAF intervention. An improvement incognitive function in the dietary guidance group was not observed until 12 months (Figure4), and although there was no diﬀerence between Group M and Group C in terms of AGE
levels in diet (Figure 2), we believe that reducing AGEs in the diet may be helpful in improving cognitive function in the long term.
The amyloid-β40/42 ratio improved in all three groups after 12 months (Figure 6). All
three groups underwent rehabilitation, including an exercise program, so there were no
significant diﬀerences in the amyloid-β40/42 ratio among the three groups after 12months, but all three groups showed a decreasing trend in the amyloid-β40/42 ratio compared to the pre-study period. Physical exercise in combination with other interventions,
including vascular risk management, diet, and cognitive training, has been found to be
associated with improved cognitive performance [2,45,46]. Among the largest improvements were those seen in cognitive functions, overall health, and mood status.

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Limitations: We originally planned to continue providing dietary guidance after 12months; however, cooperation with this guidance was diﬃcult for participants and theirfamily members, and following the guidance involved too much work and time. Since
dietary guidance was provided throughout the 12-month period, the AGE levels in thediet after 12 months were unknown. Measuring AGEs levels using self-reported dietaryintake and skin autofluorescence has limitations and potential confounding factors that
may aﬀect the accuracy of the result. The fact that the participants were in a daycare rehabilitation facility and, therefore, did not follow a uniform diet was also a factor in the ambiguous results. In addition, the advanced age of the participants made it diﬃcult for themto continue the study. Since the exercise load was not changed during the study period
and the intensity was varied according to the level of care, there were no significant differences between the groups.
In this study, we did not determine genotypes such as APOE type. The number ofparticipants was originally small, but it decreased further due to withdrawal from thestudy due to infections and a worsening of underlying diseases. In the future, we hope to
conduct a large-scale study with determinations of APOE type at residential facilities
where meals can be provided under controlled dietary conditions.
This study showed that cognitive dysfunction is multifactorial but that early intervention can prevent its worsening or even improve cognitive function. The importance ofmacrophages, the eﬀectiveness yet challenges of dietary guidance, and the importance ofsocial involvement were recognized.
5. Conclusions
Our results suggest that cognitive impairment may be prevented by dietary modification and MAF supplementation. In the present study, we were able to show that a simple explanation in an outpatient setting without strict dietary control was eﬀective, andwe were able to demonstrate eﬀectiveness by administering a supplement without drugs,
injections or other burdensome procedures with strong side eﬀects. Although there aremany limitations to this study and stronger evidence needs to be obtained from a larger
study in a setting with good dietary management, it is significant that the results could bedemonstrated with a simple intervention. MAF supplements took six months to show results, while the dietary intervention required a year to show improvement. Improving
cognition through diet requires a considerable amount of time. Although supplements
and drugs are often judged to be eﬀective over a six-month or three-month period, lifestyle
improvements such as diet may have a slower eﬀect, so it was considered necessary totake enough time for the study period. However, it is costly to continue taking supplements, and strict dietary control is diﬃcult to achieve without institutionalization or othercircumstances. Therefore, it was thought that improving diet through simple dietary guidance in a relaxed outpatient setting would be convenient for patients due to its cost andsimplicity, even if it took a long time to show eﬀects. In addition to diet and supplements,
exercise has a significant impact on cognitive function and AGEs. The amount, type, anddegree of achievement of exercise load should be considered more precisely in the future.
It was thought that it would be ideal to improve inflammation with supplements in earlystages and to improve cognition through diet in the long term, preventing cognitive decline throughout life.
Author Contributions: Y.U.-T. conceived the study, collected the data, and wrote the manuscript.
H.Y. performed the final statistical analysis. T.I. prepared the MAF supplement and placebo. All of
the authors contributed to refinement of the study protocol. All authors have read and agreed to the
published version of the manuscript.
Funding: The trial received no funding.
Institutional Review Board Statement: The trial was reviewed and approved by the Saisei Mirai
Ethics Committee (No. 2022-001, 2022/1/20).

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Informed Consent Statement: As part of the consent process, clinical study participants were informed about the risks and benefits of participating in the study. Written informed consent for investigational treatment, study data collection, analysis, and publication were obtained from all
study participants and their family members.
Data Availability Statement: The datasets generated and/or analyzed during the current study are
not publicly available considering the privacy of the participants but are available from the corresponding author upon reasonable request.
Acknowledgments: We thank Masahiko Futagami, the president of Soushinkai, and the staﬀ who
helped collect blood and data.
Conflicts of Interest: Y.U.-T. and H.Y. have no competing interests. T.I. is a director of the Inui Clinic,
which is the same group as Saisei Pharma. T.I. had no role in the design of the study; the data collection, analysis, or writing of the manuscript; or the decision regarding the results.

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